Vehicle handling models are commonly used in the design and analysis of vehicle dynamics. Especially, with the advances in vehicle control systems need for accurate and simple vehicle handling models have increased. These models have parameters, some of which are known or easily obtainable, yet some of which are unknown or difficult to obtain. These parameters are obtained by system identification, which is the study of building model from experimental data. In this thesis, identification of vehicle handling models is based on data obtained from the simulation of complex vehicle dynamics model from ADAMS representing the real vehicle and a general methodology has been developed. Identified vehicle handling models are the linear bicycle model and vehicle roll models with different tire models. Changes of sensitivity of the model outputs to model parameters with steering input frequency have been examined by sensitivity analysis to design the test input. To show that unknown parameters of the model can be identified uniquely, structural identifiability analysis has been performed. Minimizing the difference between the data obtained from the simulation of ADAMS vehicle model and the data obtained from the simulation of simple handling models by mathematical optimization methods, unknown parameters have been estimated and handling models have been identified. Estimation task has been performed using MATLAB Simulink Parameter Estimation Toolbox. By model validation it has been shown that identified handling models represent the vehicle system successfully.

Disertacijoje nagrinėjami nestacionarių matematinių modelių nestandartinėse srityse skaitiniai sprendimo algoritmai. Uždavinio formulavimo sritis yra šakotosios struktūros (ang. branching structures), kurių išsišakojimo taškuose apibrėžiami tvermės dėsniai. Tvermės dėsnių skaitinė analizė ir nestandartinių kraštinių sąlygų analizė skiria nagrinėjamus uždavinius nuo klasikinių aprašytų literatūroje matematinės fizikos uždavinių. Disertacijoje suformuluoti uždaviniai apima skaitinių algoritmų šakotose struktūrose su skirtingais srautų tvermės dėsniais stabilumo ir konvergavimo tyrimą, lygiagrečiųjų algoritmų sudarymą ir taikymą, skaitinių schemų uždaviniams su nelokaliomis integralinėmis sąlygomis tyrimą. Disertacijoje sprendžiami taikomieji neurono sužadinimo ir impulso relaksacijos lazerio apšviestame puslaidininkyje uždaviniai, netiesinio modelio identifikavimo uždavinys. Disertaciją sudaro įvadas, penki skyriai, rezultatų apibendrinimas, literatūros šaltinių sąrašas ir autorės publikacijų disertacijos tema sąrašas. Įvadiniame skyriuje formuluojama problema, aprašytas tyrimų objektas, darbo aktualumas, formuluojami darbo tikslai ir uždaviniai, aprašoma tyrimų metodika, darbo mokslinis naujumas, darbo rezultatų praktinė reikšmė, pateikti ginamieji teiginiai ir disertacijos struktūra. Pabaigoje pristatomi pranešimai konferencijose disertacijos tema. Pirmajame skyriuje pateikta matematinių modelių nestandartinėse srityse arba su nestandartinėmis sąlygomis apžvalga. Antrajame... [toliau žr. visą tekstą] / The numerical algorithms for non-stationary mathematical models in non-standard domains are investigated in the dissertation. The problem definition domain is represented by branching structures with conjugation equations considered at the branching points. The numerical analysis of the conjugation equations and non-classical boundary conditions distinguish considered problems among the classical problems of mathematical physics presented in the literature. The scope of the dissertation covers the investigation of stability and convergence of the numerical algorithms on branching structures with different conjugation equations, the construction and implementation of parallel algorithms, the investigation of the numerical schemes for the problems with nonlocal integral conditions. The modeling of the excitation of neuron and photo-excited carrier decay in a semiconductor, also the problem of the identification of nonlinear model are considered in the dissertation. The dissertation consists of an introduction, five chapters, main conclusions, bibliography and the list of the author's publications on the topic of dissertation. Introductory chapter covers the problem formulation and the object of research, the topicality of the thesis, the aims and objectives of the dissertation, the methodology of research, scientific novelty and the practical value of the achieved results. The defended thesis and structure of the dissertation are given in this chapter. The first chapter... [to full text]

Young football players are hypothesized to experience damage to the brain and brain function from repeated subconcussive head acceleration events (HAEs) during practices and games. Such damage may cause delayed cognitive and mental problems. Resting state fMRI (rs-fMRI) is an effective non-invasive method to detect alterations in brain functional connectivity. Seed-based rsfMRI analysis using the central node of the default mode network (DMN) as the seed is a common approach to measuring intrinsic changes of the DMN, accepted as a key network in brain function. Seed-based rs-fMRI analysis of the DMN was used to explore how age, HAE intensity, and HAE counts influence brain connectivity in youth athletes (ages 12-18). Middle school and high school football players and peer controls were studied using rs-fMRI before and after one season of competition. An identifiability matrix was generated from the seed-based connectivity matrix, allowing measurement of similarity between pre-season and post-season functional connectivity. The consistency of seed-based brain functional connectivity we observed across the season of play for players has no statistically significant difference from controls. The identifiability matrix exhibited no relation to the number and magnitude of any subset of HAEs experienced which rejected our hypothesis. Another finding is that high school football players exhibited the largest percentage increase in identification from middle school football players in the somatomotor network over other resting-state networks.